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Infotekmesin
Published by Politeknik Negeri Cilacap
ISSN : INFOTEKMES     EISSN : 26859858     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Mechanical Engineering
INFOTEKMESIN is a peer-reviewed open-access journal with e-ISSN 2685-9858 and p-ISSN: 2087-1627 published by Pusat Penelitian dan Pengabdian Masyarakat (P3M) Politeknik Negeri Cilacap. The journal invites scientists and engineers to exchange and disseminate theoretical and practice-oriented in the various topics include, but not limited to Informatics, electrical Engineering, and mechanical Engineering.
Arjuna Subject : -
Articles 636 Documents
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Simulasi variasi sudut lidah volute casing terhadap kecepatan aliran udara pada blower tipe forward blade Syafa‘at, Husna Endry; Kurniawan, Ipung; Ariawan, Radhi; Santoso, Agus
Infotekmesin Vol 16 No 2 (2025): Infotekmesin: Juli 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i2.2546

Abstract

Optimization of volute design is essential for the performance of centrifugal pumps and blowers. This study investigates the effect of volute tongue angle variation on air velocity and flow rate in volute casing design using flow simulations. The volute design was tested with tongue angles of 15°, 30°, 45°, 60°, and 75°, based on theoretical equations of flow rate and volute radius. Simulation results indicated that increasing the volute tongue angle enlarges the volute cross-sectional area. Generally, this enlargement decreases air velocity but increases the flow rate. A 75° tongue angle produced the highest flow rate of 4.860 m³/s, while the highest velocity, 21.35 m/s, was observed at 15°. This behavior aligns with the principle of mass conservation, where a larger cross-sectional area leads to reduced fluid velocity. These findings suggest that volute designs with larger tongue angles can optimize the flow capacity.
Pengaruh Variasi Kampuh Las dan Arus Listrik Terhadap Kekuatan Sambungan Las (Metal Inert Gas) MIG Pada Aluminium AA6063 Asrul
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2548

Abstract

Aluminium has beneficial characteristics such as corrosion resistance, heat conductivity, electrical conductivity, and lightweight. However, when looking at steel materials, aluminum has unfavorable welding properties. The selection of welding amperage and additives compatible with the parent metal can influence welding joints. The purpose of this study was to determine the effect of the strength of MIG welding joints of AA6063 aluminum alloy on the variation of groove welding with electric current. The test data shows a value equal to 1. The highest tensile test value using X camphor at an electric current of 150 amperes is 14.05 kg/mm², and the lowest tensile stress value with K camphor at a current of 155 amperes is 6.75 kg/mm². 2. The test results of the highest hardness value with the V shank at a current of 160 amperes, namely 87.09 HRB in the weld metal area, then the HAZ area decreased in hardness value, namely 76.33 HRB, and the parent metal area increased again in value, namely 78.80 HRB and 3. These results show that welding with an X shank is better than a V shank and a K shank based on the electric current in the test results.
Improving Cervical Cancer Classification Using ADASYN and Random Forest with GridSearchCV Optimization Saputra, Resha Mahardhika; Alzami, Farrikh; Pramudi, Yuventius Tyas Catur; Erawan, Lalang; Megantara, Rama Aria; Pramunendar, Ricardus Anggi; Yusuf, Moh.
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2552

Abstract

Cervical cancer is a leading cause of death among women, with over 300,000 deaths recorded in 2020. This study aims to improve the accuracy of cervical cancer diagnosis classification through a combination of Adaptive Synthetic Sampling (ADASYN) and Random Forest algorithm. The research data was obtained from the Cervical Cancer dataset in the UCI Machine Learning Repository with an imbalanced data distribution of 95% negative class and 5% positive class. ADASYN method was chosen for its ability to handle imbalanced data by focusing on minority data points that are difficult to classify. The Random Forest algorithm was optimized using GridSearchCV to achieve maximum performance. Results show that this combination improved accuracy from 96.5% to 96.8% and recall from 93.7% to 94.3%. Feature importance analysis identified key risk factors such as number of pregnancies, age at first sexual intercourse, and hormonal contraceptive use that significantly influence diagnosis. This research demonstrates the effectiveness of combining ADASYN and Random Forest in enhancing classification performance for early cervical cancer detection.
Perbandingan Random Forest dan K-Nearest Neighbors untuk Klasifikasi Body Mass Index Menggunakan SMOTE-ENN untuk Mengatasi Ketidakseimbangan Data pada Analisis Kesehatan Naufal Yogi Aptana; Ikhsan, Ali Nur; Maulana Baihaqi, Wiga; Ajeng Widiawati, Chyntia Raras
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2553

Abstract

This study aims to compare the Random Forest and K-Nearest Neighbors (KNN) algorithms in Body Mass Index (BMI) classification using the SMOTE-ENN method to address data imbalance. The dataset consists of 2111 entries with demographic and health attributes of individuals. Data imbalance poses a significant challenge that may affect the accuracy of machine learning models. The SMOTE-ENN combination was employed to improve data distribution, enabling models to recognize patterns in minority classes better. Key evaluation factors included both algorithms' accuracy, precision, recall, and F1-score. Results indicate that the Random Forest algorithm achieved higher performance with 100% accuracy than KNN with 96% after applying SMOTE-ENN. These findings highlight the unique contribution of SMOTE-ENN in handling imbalanced data, enhancing classification model quality, and significantly impacting machine learning applications in healthcare.
Perbandingan Pendekatan Machine Learning untuk Mendeteksi Serangan DDoS pada Jaringan Komputer Faiz, Muhammad Nur; Muhammad, Arif Wirawan; Sari, Laura
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2556

Abstract

Distributed Denial of Service (DDoS) attacks are a serious threat to computer network security. This study offers a comprehensive evaluation by considering accuracy, detection time, and model complexity in simulation scenarios. Using the CICDDoS2019 dataset, which includes modern attack variations and complete features, this research compares the effectiveness of Naïve Bayes (NB), Random Forest (RF), and Decision Tree (DT) algorithms in detecting DDoS attacks. The results show that RF achieves the highest accuracy (99.95%), while DT excels in recall (99.83%). These findings provide a foundation for developing hybrid ML-DL models to enhance real-time attack detection. However, limitations such as using a single dataset and offline simulations restrict the generalizability of results to real-world network conditions. This study highlights opportunities for more comprehensive future research in real-world scenarios.
Optimasi Algoritma K-Nearest Neighbors Menggunakan GridSearchCV untuk Klasifikasi Penyakit Diabetes Yaqin, Ainul; Kurniawan, Defri; Zeniarja, Junta
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2557

Abstract

Diabetes is a chronic disease that has a significant impact on global health, with prevalence increasing every year. Therefore, early detection is crucial to prevent further complications and save lives. The utilization of technology, such as machine learning, offers innovative solutions to improve the accuracy of predicting this disease. This research develops a diabetes prediction model using the K-Nearest Neighbors (KNN) algorithm with the Pima Indians Diabetes Database dataset. Given the class imbalance in the dataset, Random Over-Sampling technique was applied to balance the data distribution. The results showed that the KNN model optimized with GridSearchCV resulted in 88% accuracy, 89% precision, 75% recall, and 82% F1-score. This approach is expected to produce a more accurate and efficient model to support early detection of diabetes, and shows the great potential of machine learning technology in improving the effectiveness of disease diagnosis and control.
Rancang Bangun Angklung Elektrik dengan Mode Otomatis dan Manual Menggunakan Teknologi Mikrokontroler dan Smartphone Nur Hanafi, Ilham; Supriyono, Supriyono; Susanti , Hera
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2558

Abstract

Angklung is a traditional Indonesian musical instrument originating from West Java. Angklung is composed of two to four bamboo tubes tied with rattan ropes and played by shaking them. The existence of angklung is currently starting to be replaced by modern musical instruments. This research aims to produce angklung integrated with microcontroller and smartphone technology. The use of microcontroller technology allows angklung to be automated without changing the character of the original art. This research method uses a quantitative approach from the design stage to the final test. The research showed that angklung successfully played songs automatically and manually. The tone suitability test results reach 100%. The sound intensity test recorded an average of 86.9 dB in automatic mode and 88.2 dB in manual mode. The power consumption test shows power usage of 1,378 Watts in automatic mode and 1,461 Watts in manual mode.
Penyelidikan Kampas Rem Komposit Matriks Aluminium Diperkuat Boiler-Fly-Ash dan Silika Terhadap Nilai Densitas dan Kekerasannya Fikri, Akhmad Hasyim; Wiryono, Sukanto; Subhan, M
Infotekmesin Vol 16 No 2 (2025): Infotekmesin: Juli 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i2.2561

Abstract

This study aims to investigate the effect of the percentage of reinforcement and hot compaction pressure on the density value of Aluminum Matrix Composite brake pads, reinforced with Boiler-Fly-Ash and silica sand. The Powder Metallurgy method was used in this study, with variations in the weight fraction of reinforcement being 6%, 10%, and 14%. Mixing of the matrix powder and reinforcement was performed using a Ball Mill Machine, with a Ball Powder weight Ratio of 10:1, within 6 hours of mechanical alloying at a speed of 90 rpm. The molding process used a hot compaction system in the form of a Hydraulic Jack machine with an upper press and a lower press, with a hot pressing temperature of 350 ºC, a holding time of 10 minutes, at a pressure variation of 5200 Psi, 5600 Psi, and 6000 Psi. The sintering process used a temperature of 600 ºC at a holding temperature of 10 minutes. The density test of the specimen uses the ASTM B962-17 standard with the Archimedes theory approach, while the hardness test uses the Brinnel Hardness, referring to ASTM E110-14.  The result, the highest average density value is 2.10 g/cm³ with a reinforcement percentage variation of 10%, while the lowest density value is 1.90 g/cm³ with a reinforcement percentage of 14%. The highest hardness value is 42.93 HB with a percentage of 10%, while the lowest hardness value is 41.4 HB with a reinforcement percentage of 14% compaction of 6000 Psi
Optimalisasi Sistem Informasi Layanan Keuangan dengan Metode First Come First Served (FCFS) Purwanto, Riyadi; Dwi Novia Prasetyanti; Cahya Vikasari; Rostika Listyaningrum
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2562

Abstract

One of the important things in financial management is financial services. Cilacap State Polytechnic (PNC) is a PTN as a Work Unit. Financial management at PNC refers to applicable government regulations, but financial service policies are the authority of the leadership as a strategy to create fast, effective, and accountable financial services. The budget usage policy stipulates that work units must propose budget usage based on the Fund Withdrawal Plan through a down payment form approved by the Financial Management Officer. The current problem is that down payment forms are often scattered or lost, so the response time for payments from finance is slow, and payment queues are often not in sequence. This results in activities being hampered. This research aims to create a prototype or development design for the Financial Services Information System at PNC. The FCFS method is used as a service scheduling algorithm based on arrival time to optimize financial services. In this way, the financial service process will be more organized, the response time for financial services will be faster, and the queue for service requests will be in line.
Korelasi Nilai Oktan dan Kandungan Oksigen Biofuel Mangrove dengan Brake Torque dan Emisi NOx Mesin Bensin 150cc Syarifudin; Khumaidi Usman, Muhamad; Fatkhurrozak, Faqih; Lukman Sanjaya, Firman
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2565

Abstract

Alternative fuels are a priority to reduce the problem of fuel stock shortages. Bioethanol has potential because of its octane number specifications, oxygen content, and simple production techniques. Mangrove bioethanol is produced from mangrove fruit, which is non-edible and abundant. This study aims to observe the correlation of Mangrove Biofuel specifications (mixture of gasoline and 5% Mangrove Bioethanol) to Brake Torque and NOx Emissions produced by gasoline engines. Experimental methods are applied, from Mangrove Bioethanol production, octane value, oxygen content testing, and Mangrove Biofuel production to performance and emission testing. The results of the study showed that the correlation of the 101 octane number specifications and 30.31% oxygen content of Mangrove Biofuel increased the highest Brake Torque, reaching 5.45%, and increased the highest NOx emissions up to 6.54% at engine speeds of 5000 rpm.

Page 61 of 64 | Total Record : 636

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